Программа предсказания времени удержания пептидов с учётом посттрансляционных модификаций

This paper describes the Retention Time Predictor (RTP) program and web service for predicting the retention time of peptides on a chromatographic column in mass spectrometry experiments. Taking into account post-translational modifications of peptides the program represents a modification of the well-known SSRCalc version 3 (Krokhin, Anal. Chem. 2006, 78(22), 7785-7795). The values of retention coefficients for modified amino acid residues and the algorithm for calculating the isoelectric point value were from the pIPredict program (Skvortsov et al., Biomed. Chem. Res. Meth. 2021, 4(4), e00161). Modifications described in the program include (i) Tandem Mass Tag (TMT) and Isobaric Tags for Relative and Absolute Quantification (iTRAQ) labels; (ii) acetylation, formylation, and methylation of the N-terminal residue and/or lysine side chain; (iii) carbamidomethylation of cysteine, asparagine, and glutamic acid residues; (iv) oxidation and double oxidation of methionine and proline residues; (v) phosphorylation of serine, threonine, and tyrosine residues; (vi) C-terminal amidation of lysine and arginine residues; (vii) formation of propionamide with a cysteine residue. Retention coefficient estimation was based on data from 25 mass spectrometry experiments for which identification was performed from the raw data deposited in the ProteomeXchange database. The RTP program and web service are freely available at http://lpcit.ibmc.msk.ru/RTP.В работе представлена программа и web-сервис Retention Time Predictor (RTP), предназначенные для предсказания времени удержания пептидов на хроматографической колонке в экспериментах по масс-спектрометрии и учитывающая посттрансляционные модификации аминокислотных остатков (а.о.). Программа представляет собой модификацию известной программы SSRCalc версии 3 (Krokhin, Anal. Chem., 2006, 78(22), 7785–7795). В нее добавлены значения коэффициентов удержания для модифицированных а.о. и алгоритм расчёта величины изоэлектрической точки из программы pIPredict (Skvortsov et al., Biomed. Chem. Res. Meth., 2021, 4(4), e00161). Модификации, описанные в программе, включают: (i) Tandem Mass Tag (TMT) и Isobaric Tags for Relative and Absolute Quantification (iTRAQ) метки; (ii) ацетилирование, формилирование и метилирование N-концевого остатка и/или бокового радикала лизина; (iii) карбамидометилирование остатков цистеина, аспарагиновой и глутаминовой кислот; (iv) окисление и двойное окисление остатков метионина и пролина; (v) фосфорилирование остатков серина, треонина и тирозина; (vi) С-концевое амидирование остатков лизина и аргинина; (vii) образование пропионамида с остатком цистеина. Подбор коэффициентов удержания проведён с использованием данных 25 масс-спектрометрических экспериментов, для которых идентификация была выполнена заново по исходным (RAW) данным, депонированным в БД ProteomeXchange. Программа RTP и web-сервис свободно доступны по адресу http://lpcit.ibmc.msk.ru/RTP

Предсказание значения изоэлектрической точки пептидов и белков с широким спектром химических модификаций

The scale of virtual pKa values for calculating the isoelectric point of peptides and proteins with chemical and post-translational modifications (PTM) is presented. The learning set of pKa values is based on data from 25 experiments of isoelectric focusing of peptides with subsequent mass spectrometric identification (ProteomeXchange accession codes: PXD000065, PXD005410, PXD006291, PXD010006 and PXD017201). In order to enrich the resulting sets with peptides containing modifications the identification of peptides was repeated using raw mass spectrometry data of all datasets. In the final learning set have included peptides satisfying the following conditions: the peptide was found in the fraction with scoring function maximum and maximum peptide abundance; the peptide was found in more than one experiment, and differences of the pI value between experiments was less than 0.15 pH unit. Two variants of the scales were created. In the first variant, pKa values depended only on the residue position relative to the ends of the sequence (N- or C-terminal residue or inside the chain). In the second variant, the effect of neighboring residues was also taken into account. The prediction accuracy of the second variant was higher. The comparison with other methods of pI prediction was carried out. Although the scale was calculated from set containing only peptides, it would be applicable for pI prediction of proteins with and without PTM. The software for prediction of pI values using the resulting pKa scales is available at http://pIPredict3.ibmc.msk.ru.Представлена шкала «виртуальных» значений pKa для расчёта изоэлектрической точки пептидов и белков, имеющих как химические, так и посттрансляционные модификации (PTM). Обучающая выборка для подбора значений pKa сформирована на основе данных из 25 экспериментов по изоэлектрическому фокусирования пептидов с последующей масс-спектрометрической идентификацией (ProteomeXchange accession codes: PXD000065, PXD005410, PXD006291, PXD010006 и PXD017201). Для всех наборов данных идентификация пептидов по «сырым» масс-спектрометрическим данным проведена заново с целью обогащения выборки пептидами с модификациями. В окончательную обучающую выборку включены пептиды, для которых выполнялись следующие условия: пептид встречался во фракции, для которой величина максимума оценочной функции при идентификации пептида совпадала с максимальным значением представленности («abundance»), пептид встречался более чем в одном эксперименте, причём величина pI между экспериментами не отличалась больше чем 0.15 значений единицы pH. Созданы два варианта шкал. В первом величина pKa зависела только от его положения относительно концов последовательности (N- или C-концевой остаток, либо внутри цепи). Во втором учитывали также влияние соседних остатков. Точность предсказания по второму варианту была выше. Проведено сравнение с другими методами предсказания pI. Несмотря на то, что шкала рассчитывалась по выборке, содержащей только пептиды, она применима и для предсказания pI белков как с наличием PTM, так и без. Создано программное обеспечение для предсказания pI с использованием полученных шкал pKa, доступное по адресу http://pIPredict3.ibmc.msk.ru

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Learning with the use of distance learning technologies or what digital tools should a teacher possess?

This work is devoted to the analysis of the digital tools that a modern teacher should possess to implement the educational process using distance learning technologies. Based on the conducted research, the main competencies that a teacher should have to conduct professional activities from the point of view of students were established. Digital tools are urgently needed to implement these competencies. In this paper, we will show our view on the algorithm for using digital tools in the educational process. A teacher should have a wide arsenal of digital tools: be able to use office programs, be able to search, to select, to analyze and to interpret information. To be able to create a teacher’s website, record digital audio and video content, to be able to place it for easy access for students, and, of course, be able to use the University’s learning management system

About the substantiation of diagnostic indices in different categories of juveniles with delinquent behavior within the authority of the psychological, medical and educational committee

The problems of developing diagnostic indices, which could differentiate categories of deviant behavior in children and adolescents in the context of psychological, medical and educational committees’ (PMEC) activities are considered. The main goal of PMEC is timely detection of children with peculiarities in their physical and / or mental development and / or behavior deviation, their complex psychological, medical and educational examination and, on the basis of its results, development of recommendations for the corresponding assistance and organization of their education. This group of minors includes children and adolescents not only with limited health conditions, but also with different kinds of deviant behavior and in conflict with the law. In the article, the analysis of pupils’ personal files from special closed educational institutions for minors in conflict with the law is presented. The methodical instrument for the structured assessment of a child’s social situation of development in the work of a PMEC approved in the framework of the project “Development of scientific-methodical provisions for the PMEC work concerning examination and producing recommendations for pupils with deviant behavior and in conflict with the law” is described and used

Hair Trace Element and Electrolyte Content in Women with Natural and In Vitro Fertilization-Induced Pregnancy

The objective of the present study was to perform comparative analysis of hair trace element content in women with natural and in vitro fertilization (IVF)-induced pregnancy. Hair trace element content in 33 women with IVF-induced pregnancy and 99 age- and body mass index-matched control pregnant women (natural pregnancy) was assessed using inductively coupled plasma mass spectrometry. The results demonstrated that IVF-pregnant women are characterized by significantly lower hair levels of Cu, Fe, Si, Zn, Ca, Mg, and Ba at p < 0.05 or lower. Comparison of the individual levels with the national reference values demonstrated higher incidence of Fe and Cu deficiency in IVF-pregnant women in comparison to that of the controls. IVF pregnancy was also associated with higher hair As levels (p < 0.05). Multiple regression analysis revealed a significant interrelation between IVF pregnancy and hair Cu, Fe, Si, and As content. Hair Cu levels were also influenced by vitamin/mineral supplementation and the number of pregnancies, whereas hair Zn content was dependent on prepregnancy anthropometric parameters. In turn, planning of pregnancy had a significant impact on Mg levels in scalp hair. Generally, the obtained data demonstrate an elevated risk of copper, iron, zinc, calcium, and magnesium deficiency and arsenic overload in women with IVF-induced pregnancy. The obtained data indicate the necessity of regular monitoring of micronutrient status in IVF-pregnant women in order to prevent potential deleterious effects of altered mineral homeostasis. © 2017, Springer Science+Business Media New York